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Is it possible to predict who will develop Alzheimer’s disease simply by looking at writing patterns years before symptoms appear?
According to a new study by researchers at IBM, the answer is yes.
And, they and others say Alzheimer’s disease is just the beginning. People with a wide variety of neurological diseases have distinctive speech patterns that investigators suspect may serve as warning signs of their disease.
For the Alzheimer’s disease study, the researchers looked at a group of 80 men and women in their 80s – half had Alzheimer’s disease and the rest did not. But, seven and a half years earlier, everything was cognitively normal.
Both men and women participated in the Framingham Heart Study, a long-standing federal research effort that requires regular physical and cognitive testing. As part of it, they took a handwriting test before one of them developed Alzheimer’s disease which asks subjects to describe the drawing of a boy standing on an unstable stool and looking for a cookie jar on a high shelf as a woman turns her back to him. , is unconscious of an overflowing sink.
The researchers examined the subjects’ word usage with an artificial intelligence program that looked for subtle differences in language. He identified a group of subjects who were more repetitive in their use of words during that earlier era when all were cognitively normal. These subjects also made mistakes, such as spelling words or improper capitalization, and they used telegraphic language, that is, language that has a simple grammatical structure and lacks subjects. and words like “the”, “is” and “are”.
Members of this group turned out to be the people who developed Alzheimer’s disease.
The AI program predicted, with 75% accuracy, who would get Alzheimer’s disease, according to results recently published in The Lancet EClinicalMedicine.
“We had no prior assumption that the use of the words would show anything,” said Ajay Royyuru, vice president of healthcare and life sciences research at IBM Thomas J. Watson Research Center in Yorktown Heights, NY, where the AI analysis was performed.
Alzheimer’s researchers were puzzled, saying that where there are ways to slow or stop the disease – a goal that so far has remained elusive – it will be important to have simple tests that can warn, soon. the onset, that without intervention, a person will develop brain disease.
“What’s going on here is very smart,” said Dr. Jason Karlawish, Alzheimer’s researcher at the University of Pennsylvania. “Given a large volume of oral or written speech, can you send a signal?”
For years, researchers have analyzed speech and voice changes in people with symptoms of neurological diseases – Alzheimer’s, ALS, Parkinson’s, frontotemporal dementia, bipolar, and schizophrenia, among others.
But, said Dr Michael Weiner, who studies Alzheimer’s disease at the University of California at San Francisco, the IBM report breaks new ground.
“This is the first report I’ve seen that took people who are quite normal and predicted with some precision who would have problems years later,” he said.
The hope is to expand Alzheimer’s work to find subtle changes in language use by people without obvious symptoms but who will go on to develop other neurological diseases.
Each neurological disease produces unique changes in speech, which likely occur long before the time of diagnosis, said Dr. Murray Grossman, professor of neurology at the University of Pennsylvania and director of the university’s Frontotemporal Dementia Center.
He studied speech in patients with a behavioral form of frontotemporal dementia, a disorder caused by the progressive loss of nerves in the frontal lobes of the brain. These patients exhibit apathy and impaired judgment, self-control, and empathy that have proven difficult to objectively quantify.
Speech is different, Dr Grossman said, because changes can be measured.
At the beginning of the course of this disease, there are changes in the rate of speech of the patients, with pauses distributed seemingly at random. Word usage is also changing – patients use fewer abstract words.
These alterations are directly related to changes in the frontotemporal parts of the brain, Dr. Grossman said. And they seem to be universal, not unique to English.
Dr. Adam Boxer, director of the Clinical Neuroscience Research Unit at the University of California, San Francisco, is also studying frontotemporal dementia. Its tool is a smartphone application. Its subjects are healthy people who have inherited a genetic predisposition to develop the disease. His method consists of showing subjects a picture and asking them to record a description of what they see.
“We want to measure changes very early on, five to 10 years before they show symptoms,” he said.
“The good thing about smartphones,” Dr Boxer added, “is that you can do all kinds of things.” Researchers can ask people to talk for a minute about something that happened that day, he said, or to repeat sounds like tatatatata.
Dr Boxer said he and others focused on speaking because they wanted inexpensive, non-invasive testing.
Dr Cheryl Corcoran, a psychiatrist at the Icahn School of Medicine at Mount Sinai in New York City, hopes to use the language changes to predict which adolescents and young adults at high risk for schizophrenia might develop the disease.
Medicines to treat schizophrenia can help those who will develop the disease, but the challenge is to identify who the patients will be. A quarter of people with occasional symptoms have seen them go away, and about a third have never progressed to schizophrenia although their occasional symptoms persist.
Guillermo Cecchi, an IBM researcher who was also involved in recent Alzheimer’s disease research, studied speech in 34 of Dr. Corcoran’s patients, looking for “brain drain”. i.e. cases where patients were late when talking and wiping ideas in different directions. He also researched “poverty of speech”, that is, the use of simple syntactic structures and short sentences.
Additionally, Dr Cecchi and his colleagues studied another small group of 96 patients in Los Angeles – 59 of whom had occasional delusions. The rest were healthy people and people with schizophrenia. He asked these subjects to tell a story they had just heard, and he looked for the same revealing speech patterns.
In both groups, the artificial intelligence program was able to predict, with 85% accuracy, which subjects developed schizophrenia three years later.
“Many small studies have found the same signals,” said Dr Corcoran. At this point, she said, “we’re not yet at the point where we can tell people whether they’re at risk or not.”
Dr Cecchi is encouraged, although he realizes the studies are still in their infancy.
“For us, it’s a priority to do science well and on a large scale,” he said. “We should have a lot more samples. There are over 60 million psychiatric interviews in the United States each year, but none of these interviews use the tools we have.
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